Cutting Through the Noise: Improving Weakly Supervised Machine Learning for Practical Applications
Esteban Safranchik hopes to harness the potential of weakly supervised machine learning to impact fields beyond computer science. Now a PhD student at the University of Washington, Esteban got his start in research as an undergraduate at Brown University. His work was published at the 2020 Association for the Advancement of Artificial Intelligence (AAAI) Conference and is also used by economists and data scientists.